IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v31y2020i7d10.1007_s10845-020-01537-6.html
   My bibliography  Save this article

Transfer-robot task scheduling in flexible job shop

Author

Listed:
  • Andy Ham

    (Liberty University)

Abstract

This paper studies a simultaneous scheduling of production and material transfer in a flexible job shop environment. The simultaneous scheduling approach has been recently adopted by a robotic mobile fulfillment system, wherein transbots pick up jobs and deliver to pick-stations for processing, which requires a simultaneous scheduling of jobs, transbots, and stations. Two different constraint programming formulations are proposed for the first time for a flexible job shop scheduling problem with transbots, significantly outperforming all other benchmark approaches in the literature and proving optimality of the well-known benchmark instances.

Suggested Citation

  • Andy Ham, 2020. "Transfer-robot task scheduling in flexible job shop," Journal of Intelligent Manufacturing, Springer, vol. 31(7), pages 1783-1793, October.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:7:d:10.1007_s10845-020-01537-6
    DOI: 10.1007/s10845-020-01537-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-020-01537-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-020-01537-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Silviu Raileanu & Florin Anton & Alexandru Iatan & Theodor Borangiu & Silvia Anton & Octavian Morariu, 2017. "Resource scheduling based on energy consumption for sustainable manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1519-1530, October.
    2. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    3. Ümit Bilge & Gündüz Ulusoy, 1995. "A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS," Operations Research, INFORMS, vol. 43(6), pages 1058-1070, December.
    4. Dalila B. M. M. Fontes & Seyed Mahdi Homayouni, 2019. "Joint production and transportation scheduling in flexible manufacturing systems," Journal of Global Optimization, Springer, vol. 74(4), pages 879-908, August.
    5. Olatunde T. Baruwa & Miquel A. Piera, 2016. "A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4773-4792, August.
    6. Lamballais, T. & Roy, D. & De Koster, M.B.M., 2017. "Estimating performance in a Robotic Mobile Fulfillment System," European Journal of Operational Research, Elsevier, vol. 256(3), pages 976-990.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Park, Myoung-Ju & Ham, Andy, 2022. "Energy-aware flexible job shop scheduling under time-of-use pricing," International Journal of Production Economics, Elsevier, vol. 248(C).
    2. Berterottière, Lucas & Dauzère-Pérès, Stéphane & Yugma, Claude, 2024. "Flexible job-shop scheduling with transportation resources," European Journal of Operational Research, Elsevier, vol. 312(3), pages 890-909.
    3. Jingyang Xiang & Lianguo Wang & Li Li & Kee-Hung Lai & Wei Cai, 2024. "Classification-design-optimization integrated picking robots: a review," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 2979-3002, October.
    4. Sun, Yige & Chung, Sai-Ho & Wen, Xin & Ma, Hoi-Lam, 2021. "Novel robotic job-shop scheduling models with deadlock and robot movement considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    5. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
    6. Fatemi-Anaraki, Soroush & Tavakkoli-Moghaddam, Reza & Foumani, Mehdi & Vahedi-Nouri, Behdin, 2023. "Scheduling of Multi-Robot Job Shop Systems in Dynamic Environments: Mixed-Integer Linear Programming and Constraint Programming Approaches," Omega, Elsevier, vol. 115(C).
    7. Xiao Han & Huarui Wu & Huaji Zhu & Jingqiu Gu & Wei Guo & Yisheng Miao, 2024. "Scheduling of Collaborative Vegetable Harvesters and Harvest-Aid Vehicles on Farms," Agriculture, MDPI, vol. 14(9), pages 1-20, September.
    8. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2021. "Production and transport scheduling in flexible job shop manufacturing systems," Journal of Global Optimization, Springer, vol. 79(2), pages 463-502, February.
    2. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
    3. Arash Amirteimoori & Reza Kia, 2023. "Concurrent scheduling of jobs and AGVs in a flexible job shop system: a parallel hybrid PSO-GA meta-heuristic," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 727-753, September.
    4. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.
    5. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
    6. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.
    7. Dalila B. M. M. Fontes & S. Mahdi Homayouni & Mauricio G. C. Resende, 2022. "Job-shop scheduling-joint consideration of production, transport, and storage/retrieval systems," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1284-1322, September.
    8. Dalila B. M. M. Fontes & Seyed Mahdi Homayouni, 2019. "Joint production and transportation scheduling in flexible manufacturing systems," Journal of Global Optimization, Springer, vol. 74(4), pages 879-908, August.
    9. Moussa Abderrahim & Abdelghani Bekrar & Damien Trentesaux & Nassima Aissani & Karim Bouamrane, 2020. "Manufacturing 4.0 Operations Scheduling with AGV Battery Management Constraints," Energies, MDPI, vol. 13(18), pages 1-19, September.
    10. João M. R. C. Fernandes & Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2022. "Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review," Sustainability, MDPI, vol. 14(10), pages 1-34, May.
    11. Jianxun Li & Wenjie Cheng & Kin Keung Lai & Bhagwat Ram, 2022. "Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging," Mathematics, MDPI, vol. 10(19), pages 1-15, September.
    12. Khayat, Ghada El & Langevin, Andre & Riopel, Diane, 2006. "Integrated production and material handling scheduling using mathematical programming and constraint programming," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1818-1832, December.
    13. Roy, Debjit & Nigam, Shobhit & de Koster, René & Adan, Ivo & Resing, Jacques, 2019. "Robot-storage zone assignment strategies in mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 119-142.
    14. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    15. Ganesan, Viswanath Kumar & Sivakumar, Appa Iyer, 2006. "Scheduling in static jobshops for minimizing mean flowtime subject to minimum total deviation of job completion times," International Journal of Production Economics, Elsevier, vol. 103(2), pages 633-647, October.
    16. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    17. Ramalhinho Lourenco, Helena, 1996. "Sevast'yanov's algorithm for the flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 176-189, May.
    18. Jiuh‐Biing Sheu & Tsan‐Ming Choi, 2023. "Can we work more safely and healthily with robot partners? A human‐friendly robot–human‐coordinated order fulfillment scheme," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 794-812, March.
    19. Taudes, Alfred & Trcka, Michael & Lukanowicz, Martin, 2002. "Organizational learning in production networks," Journal of Economic Behavior & Organization, Elsevier, vol. 47(2), pages 141-163, February.
    20. D J Stewardson & R I Whitfield, 2004. "A demonstration of the utility of fractional experimental design for finding optimal genetic algorithm parameter settings," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 132-138, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:31:y:2020:i:7:d:10.1007_s10845-020-01537-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.